In recent years, advances in technology, as well as ever evolving tastes in style, have led to substantial changes in the design of automobiles. Electric motors (or electric machines) are finding an increasing number of applications in the automotive industry due to the electrification of the automotive drive system. Electric and/or hybrid vehicles utilize electric motors as either primary or supplemental torque sources in the automotive drive system. These electric motors are expected to function over extreme operating conditions for an extended period of time with high reliability. However, over time, the operating stresses applied to the electric motor may degrade the condition of the stator windings. For example, thermal stress and/or voltage stress may lead to insulation breakdown, which in turn, may result in partial short-circuiting and/or open-circuiting of individual turns of the stator windings. Accordingly, it is desirable to detect degradation in the stator windings to facilitate maintenance of the motor and ensure reliable operation of the motor throughout the lifetime of the vehicle.
To diagnose the stator windings, some common prior art techniques utilize voltage injection (or current injection), which may potentially influence the operation of the motor. Alternative techniques use Fourier-based analysis or other frequency-domain analysis, which require relatively greater computational resources and corresponding delays in response time. Neural network-based diagnostic techniques have been proposed, however, these are often limited to a particular type of motor and/or require an undesirable amount of time and/or data to train the neural network (e.g., machine learning). Accordingly, it is desirable to provide systems and methods that allow for fault conditions in stator windings to be identified as quickly as possible without requiring a significant increase in computational resources or potentially interfering with otherwise normal operation of the motor. Furthermore, other desirable features and characteristics of the present invention will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the foregoing technical field and background.